LSTM in Algorithmic Investment Strategies on BTC and S&P500 Index [PDF]
Sensors, 2022 We use LSTM networks to forecast the value of the BTC and S&P500 index, using data from 2013 to the end of 2020, with the following frequencies: daily, 1 h, and 15 min data.
Jakub Michańków +2 more
doaj +8 more sources
Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index [PDF]
Entropy, 2022 This research aims to compare the performance of ARIMA as a linear model with that of the combination of ARIMA and GARCH family models to forecast S&P500 log returns in order to construct algorithmic investment strategies on this index.
Nguyen Vo, Robert Ślepaczuk
doaj +8 more sources
Optimization of investment strategies through machine learning
Heliyon, 2023 The main objective of this research is to develop a sustainable stock quantitative investing model based on Machine Learning and Economic Value-Added techniques for optimizing investment strategies.
Jiaqi Li +4 more
doaj +3 more sources
Artificial intelligence for precision malaria control: transforming surveillance, prediction, and intervention strategies [PDF]
Frontiers in Digital HealthMalaria elimination has stalled globally despite decades of investment, with traditional surveillance constrained by retrospective reporting and limited capacity to integrate high-dimensional, non-linear data.
Mohamed Sharif Abdi +12 more
doaj +2 more sources
LSTM-ARIMA as a hybrid approach in algorithmic investment strategies
Knowledge-Based SystemsThis study focuses on building an algorithmic investment strategy employing a hybrid approach that combines LSTM and ARIMA models referred to as LSTM-ARIMA. This unique algorithm uses LSTM to produce final predictions but boost results of this RNN by adding the residuals obtained from ARIMA predictions among other inputs. The algorithm is tested across
Robert Ślepaczuk
exaly +3 more sources
Optimization of Cryptocurrency Algorithmic Trading Strategies Using the Decomposition Approach
Big Data and Cognitive Computing, 2023 A cryptocurrency is a non-centralized form of money that facilitates financial transactions using cryptographic processes. It can be thought of as a virtual currency or a payment mechanism for sending and receiving money online.
Sherin M. Omran +2 more
doaj +3 more sources
Algorithmic Trading and Efficiency of the Stock Market in Poland
Finanse i Prawo Finansowe, 2021 The aim of the article is to investigate the impact of algorithmic trading on the returns obtained in the context of market efficiency theory. The research hypothesis is that algorithmic trading can contribute to a better rate of return than when using ...
Rafał Jóźwicki +2 more
doaj +1 more source
Application of machine learning in algorithmic investment strategies on global stock markets
Research in International Business and Finance, 2023 Robert Ślepaczuk
exaly +2 more sources
Flexible Decision Support System for Algorithmic Trading: Empirical Application on Crude Oil Markets
IEEE Access, 2022 Generating reliable trading signals is a challenging task for financial market professionals. This research designs a novel decision-support system (DSS) for algorithmic trading and applies it empirically on two main crude oil markets.
Cristiana Tudor, Robert Sova
doaj +1 more source
LSTM-Based Deep Model for Investment Portfolio Assessment and Analysis
Applied Bionics and Biomechanics, 2022 In recent years, within the scope of financial quantification, quantitative investment models that support human-oriented algorithms have been proposed. These models attempt to characterize fiat-delayed series through intelligent acquaintance methods to ...
Haohua Yang
doaj +1 more source